Research On Energy Saving Operation Model And Intelligent Optimization Method Of High Speed Train

Rail transportation has an important strategic significance in the modernization of our country,and the people of China are the most universal and wide range of long-range travel choices,and the relative economic and security measures in the traditional transportation industry.In addition,energy consumption due to the development of high-speed construction of the railway industry is immeasurable,and in this context,it is very important to study the energy-saving operation of trains.In this paper,as the starting point of energy consumption of high-speed train,the algorithm was improved by connecting features of train operation to two smart algorithms with wide adaptability.Includes three main areas:First,we performed a force analysis for the train running,and constructed a single mass kinematics model of the high-speed train by obtaining train traction formula.The method of calculating the stress such as train stress and distance and speed in different modes was summarized.With the minimum function of energy consumption as a target function,other restrictions such as the speed distance in train operation were changed to the punishment.Count the number and solve with the algorithm.Second,the improvement of genetic algorithm and particle swarm algorithm is presented.For the genetic algorithm,we propose an excellent function of three generations to improve the stochastic expression in the algorithm and to look for such an excellent guided mechanism,and improve the efficiency of the algorithm solution.An inverse operator is simultaneously introduced to increase the solution space of the algorithm.Based on the particle swarm algorithm,an improved simulated annealing-particle swarm algorithm is proposed to solve the particle group defects,improving the particle position updating strategy,improving two adjustable parameters in the particle group,and improving the accuracy of the solution.Finally,by the train parameter simulation of actual CRH3,matlab verifies the effectiveness of the algorithm in this paper,selects the complex line with the slope and the tunnel in actual operation,simulates the train operation control,and the train satisfies the constraint under different conditions.At the same time,the convergence rate was faster and the energy saving effect was realized.